Abstract
This paper investigates the possibility of using information from brain signals, obtained through a light and inexpensive Brain Computer Interface (BCI), in order to dynamically adjust the difficulty of an educational video game and adapt the level of challenge to players’ abilities. In this experiment, attention levels of Tetris players – measured with the BCI – have been evaluated as a function of game difficulty. Processing of the data revealed that both in intra- and inter- player analysis, an increase in game difficulty was followed by an increase in attention. These results come in accordance with similar experiments performed with a 19 sensor EEG cap, as opposed to the single-dry-sensor BCI used here. These findings give new possibilities in the development of educational games that adapt to the mental state of player/learner.
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Patsis, G., Sahli, H., Verhelst, W., De Troyer, O. (2013). Evaluation of Attention Levels in a Tetris Game Using a Brain Computer Interface. In: Carberry, S., Weibelzahl, S., Micarelli, A., Semeraro, G. (eds) User Modeling, Adaptation, and Personalization. UMAP 2013. Lecture Notes in Computer Science, vol 7899. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38844-6_11
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DOI: https://doi.org/10.1007/978-3-642-38844-6_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38843-9
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